Division-of-focal-plane (DoFP) polarimeters for the visible spectrum hold the promise of being able to capture both the
angle and degree of linear polarization in real-time and at high spatial resolution. These sensors are realized by monolithic
integration of CCD imaging elements with metallic nanowire polarization filter arrays at the focal plane of the sensor.
These sensors capture large amounts of raw polarization data and present unique computational challenges as they aim
to provide polarimetric information at high spatial and temporal resolutions. The image processing pipeline in a typical
DoFP polarimeter is: per-pixel calibration, interpolation of the four sub-sampled polarization pixels, Stokes parameter
estimation, angle and degree of linear polarization estimation, and conversion from polarization domain to color space
for display purposes. The entire image processing pipeline must operate at the same frame rate as the CCD polarization
imaging sensor (40 frames per second) or higher in order to enable real-time extraction of the polarization properties from
the imaged environment. To achieve the necessary frame rate, we have implemented and evaluated the image processing
pipeline on three different platforms: general purpose CPU, graphics processing unit (GPU), and an embedded FPGA. The
computational throughput, power consumption, precision and physical limitations of the implementations on each platform
are described in detail and experimental data is provided.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Timothy York ; Samuel Powell and Viktor Gruev
A comparison of polarization image processing across different platforms
", Proc. SPIE 8160, Polarization Science and Remote Sensing V, 816004 (September 9, 2011); doi:10.1117/12.894633; http://dx.doi.org/10.1117/12.894633